journal article·2013-03-20

Synergy of Pickering Emulsion and Sol‐Gel Process for the Construction of an Efficient, Recyclable Enzyme Cascade System

Jiafu Shi, Xiaoli Wang, Wenyan Zhang, Zhongyi Jiang, Yanpeng Liang, Yuanyuan Zhu, Chunhong Zhang

Advanced Functional Materials· Volume 23· Issue 11
Publisher page

Abstract

Abstract An efficient, easily recyclable enzyme cascade system based on nanoparticle‐stabilized capsules (NPSCs) is constructed through a synergy of a Pickering emulsion and sol‐gel process. Specifically, oligodopa‐coated titania nanoparticles (biomimetic titania) containing the first enzyme (FateDH) are synthesized through a bioadhesion‐assisted biomimetic mineralization approach. The biomimetic titania is then spontaneously assembled at the interface between the oil phase (hexadecane/butyl titanate (BuTi) mixture) and water phase during the formation of Pickering emulsions. The sol‐gel process of BuTi can produce not only butanol for assisting the formation of Pickering emulsions but also titania gel particles (sol‐gel titania) for cross‐linking the biomimetic titania through catechol‐titanium chelating. The NPSCs obtained, which contain the first enzyme, conjugate the second enzyme (FaldDH) onto the surface for constructing the enzyme cascade system. The system exhibits high activity and stability, particularly, superior recyclability for conversion of CO2 into formaldehyde. In detail, the system shows a formaldehyde yield of 50.0%, and can quickly float onto the air/water interface soon after stopping the agitation of reaction mixtures, which ensures that the formaldehyde yield keeps almost unaltered after 10 times recycling. This study will be useful for facile construction of a wealth of catalytic systems with efficient, recyclable attributes.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Pickering emulsions and particle stabilization · Algal biology and biofuel production · Mesoporous Materials and Catalysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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